From cc4cc182580b0fb3e458dc0e848957640d87ad87 Mon Sep 17 00:00:00 2001
From: Laurent COLBOIS <lcolbois@.idiap.ch>
Date: Wed, 12 May 2021 13:53:31 +0200
Subject: [PATCH] Refactoring DNN baselines which only differ by the specific
extractor
---
.../config/baseline/arcface_insightface.py | 31 ++---------
.../config/baseline/facenet_sanderberg.py | 28 ++--------
bob/bio/face/config/baseline/helpers.py | 2 -
.../inception_resnetv1_casiawebface.py | 27 ++--------
.../baseline/inception_resnetv1_msceleb.py | 28 ++--------
.../inception_resnetv2_casiawebface.py | 28 ++--------
.../baseline/inception_resnetv2_msceleb.py | 27 ++--------
.../mobilenetv2_msceleb_arcface_2021.py | 32 ++---------
.../baseline/resnet50_msceleb_arcface_2021.py | 32 ++---------
.../baseline/resnet50_vgg2_arcface_2021.py | 33 ++----------
bob/bio/face/config/baseline/templates.py | 53 +++++++++++++++++++
.../config/baseline/tf2_inception_resnet.py | 31 ++---------
12 files changed, 97 insertions(+), 255 deletions(-)
create mode 100644 bob/bio/face/config/baseline/templates.py
diff --git a/bob/bio/face/config/baseline/arcface_insightface.py b/bob/bio/face/config/baseline/arcface_insightface.py
index db164c30..4e2975fb 100644
--- a/bob/bio/face/config/baseline/arcface_insightface.py
+++ b/bob/bio/face/config/baseline/arcface_insightface.py
@@ -1,41 +1,18 @@
from bob.bio.face.embeddings.mxnet_models import ArcFaceInsightFace
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import arcface_baseline
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (112, 112)
- if annotation_type == "eyes-center":
- # Hard coding eye positions for backward consistency
- cropped_positions = {
- "leye": (55, 81),
- "reye": (55, 42),
- }
- else:
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return arcface_baseline(
embedding=ArcFaceInsightFace(memory_demanding=memory_demanding),
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/facenet_sanderberg.py b/bob/bio/face/config/baseline/facenet_sanderberg.py
index bdefacb8..3197d061 100644
--- a/bob/bio/face/config/baseline/facenet_sanderberg.py
+++ b/bob/bio/face/config/baseline/facenet_sanderberg.py
@@ -1,39 +1,19 @@
from bob.bio.face.embeddings.tf2_inception_resnet import (
FaceNetSanderberg_20170512_110547,
)
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
-
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import facenet_baseline
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (160, 160)
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
-
- # ASSEMBLE TRANSFORMER
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return facenet_baseline(
embedding=FaceNetSanderberg_20170512_110547(memory_demanding=memory_demanding),
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
- annotator="mtcnn",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/helpers.py b/bob/bio/face/config/baseline/helpers.py
index 0daeaf09..1ea0668e 100644
--- a/bob/bio/face/config/baseline/helpers.py
+++ b/bob/bio/face/config/baseline/helpers.py
@@ -1,6 +1,4 @@
-import bob.bio.face
from sklearn.pipeline import make_pipeline
-from bob.bio.base.wrappers import wrap_sample_preprocessor
from bob.pipelines import wrap
from bob.bio.face.helpers import face_crop_solver
import numpy as np
diff --git a/bob/bio/face/config/baseline/inception_resnetv1_casiawebface.py b/bob/bio/face/config/baseline/inception_resnetv1_casiawebface.py
index b532c815..0d88bbad 100644
--- a/bob/bio/face/config/baseline/inception_resnetv1_casiawebface.py
+++ b/bob/bio/face/config/baseline/inception_resnetv1_casiawebface.py
@@ -1,40 +1,21 @@
from bob.bio.face.embeddings.tf2_inception_resnet import (
InceptionResnetv1_Casia_CenterLoss_2018,
)
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import facenet_baseline
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (160, 160)
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
-
- # ASSEMBLE TRANSFORMER
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return facenet_baseline(
embedding=InceptionResnetv1_Casia_CenterLoss_2018(
memory_demanding=memory_demanding
),
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
- annotator="mtcnn",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/inception_resnetv1_msceleb.py b/bob/bio/face/config/baseline/inception_resnetv1_msceleb.py
index db94eddd..766f1cf2 100644
--- a/bob/bio/face/config/baseline/inception_resnetv1_msceleb.py
+++ b/bob/bio/face/config/baseline/inception_resnetv1_msceleb.py
@@ -1,40 +1,22 @@
from bob.bio.face.embeddings.tf2_inception_resnet import (
InceptionResnetv1_MsCeleb_CenterLoss_2018,
)
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import facenet_baseline
+
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (160, 160)
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
-
- # ASSEMBLE TRANSFORMER
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return facenet_baseline(
embedding=InceptionResnetv1_MsCeleb_CenterLoss_2018(
memory_demanding=memory_demanding
),
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
- annotator="mtcnn",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/inception_resnetv2_casiawebface.py b/bob/bio/face/config/baseline/inception_resnetv2_casiawebface.py
index c20d856c..1f56b451 100644
--- a/bob/bio/face/config/baseline/inception_resnetv2_casiawebface.py
+++ b/bob/bio/face/config/baseline/inception_resnetv2_casiawebface.py
@@ -1,40 +1,22 @@
from bob.bio.face.embeddings.tf2_inception_resnet import (
InceptionResnetv2_Casia_CenterLoss_2018,
)
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import facenet_baseline
+
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (160, 160)
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
-
- # ASSEMBLE TRANSFORMER
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return facenet_baseline(
embedding=InceptionResnetv2_Casia_CenterLoss_2018(
memory_demanding=memory_demanding
),
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
- annotator="mtcnn",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/inception_resnetv2_msceleb.py b/bob/bio/face/config/baseline/inception_resnetv2_msceleb.py
index d44585eb..2a4bd3d1 100644
--- a/bob/bio/face/config/baseline/inception_resnetv2_msceleb.py
+++ b/bob/bio/face/config/baseline/inception_resnetv2_msceleb.py
@@ -1,40 +1,21 @@
from bob.bio.face.embeddings.tf2_inception_resnet import (
InceptionResnetv2_MsCeleb_CenterLoss_2018,
)
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import facenet_baseline
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (160, 160)
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
-
- # ASSEMBLE TRANSFORMER
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return facenet_baseline(
embedding=InceptionResnetv2_MsCeleb_CenterLoss_2018(
memory_demanding=memory_demanding
),
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
- annotator="mtcnn",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/mobilenetv2_msceleb_arcface_2021.py b/bob/bio/face/config/baseline/mobilenetv2_msceleb_arcface_2021.py
index 2ca17ebe..61b9db98 100644
--- a/bob/bio/face/config/baseline/mobilenetv2_msceleb_arcface_2021.py
+++ b/bob/bio/face/config/baseline/mobilenetv2_msceleb_arcface_2021.py
@@ -1,41 +1,19 @@
from bob.bio.face.embeddings.mobilenet_v2 import MobileNetv2_MsCeleb_ArcFace_2021
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import arcface_baseline
+
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (112, 112)
- if annotation_type == "eyes-center":
- # Hard coding eye positions for backward consistency
- cropped_positions = {
- "leye": (55, 81),
- "reye": (55, 42),
- }
- else:
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return arcface_baseline(
embedding=MobileNetv2_MsCeleb_ArcFace_2021(memory_demanding=memory_demanding),
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/resnet50_msceleb_arcface_2021.py b/bob/bio/face/config/baseline/resnet50_msceleb_arcface_2021.py
index c5056662..442247b5 100644
--- a/bob/bio/face/config/baseline/resnet50_msceleb_arcface_2021.py
+++ b/bob/bio/face/config/baseline/resnet50_msceleb_arcface_2021.py
@@ -1,42 +1,18 @@
from bob.bio.face.embeddings.resnet50 import Resnet50_MsCeleb_ArcFace_2021
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import arcface_baseline
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (112, 112)
- if annotation_type == "eyes-center":
- # Hard coding eye positions for backward consistency
- cropped_positions = {
- "leye": (55, 81),
- "reye": (55, 42),
- }
- else:
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
-
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return arcface_baseline(
embedding=Resnet50_MsCeleb_ArcFace_2021(memory_demanding=memory_demanding),
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/resnet50_vgg2_arcface_2021.py b/bob/bio/face/config/baseline/resnet50_vgg2_arcface_2021.py
index 05eaa49b..95a3a95b 100644
--- a/bob/bio/face/config/baseline/resnet50_vgg2_arcface_2021.py
+++ b/bob/bio/face/config/baseline/resnet50_vgg2_arcface_2021.py
@@ -1,41 +1,18 @@
from bob.bio.face.embeddings.resnet50 import Resnet50_VGG2_ArcFace_2021
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import arcface_baseline
+
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (112, 112)
- if annotation_type == "eyes-center":
- # Hard coding eye positions for backward consistency
- cropped_positions = {
- "leye": (55, 81),
- "reye": (55, 42),
- }
- else:
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
-
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return arcface_baseline(
embedding=Resnet50_VGG2_ArcFace_2021(memory_demanding=memory_demanding),
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
diff --git a/bob/bio/face/config/baseline/templates.py b/bob/bio/face/config/baseline/templates.py
new file mode 100644
index 00000000..bf6c6c4f
--- /dev/null
+++ b/bob/bio/face/config/baseline/templates.py
@@ -0,0 +1,53 @@
+from bob.bio.face.config.baseline.helpers import (
+ dnn_default_cropping,
+ embedding_transformer,
+)
+from bob.bio.base.pipelines.vanilla_biometrics import (
+ Distance,
+ VanillaBiometricsPipeline,
+)
+
+
+def arcface_baseline(embedding, annotation_type, fixed_positions=None):
+ # DEFINE CROPPING
+ cropped_image_size = (112, 112)
+ if annotation_type == "eyes-center":
+ # Hard coding eye positions for backward consistency
+ cropped_positions = {
+ "leye": (55, 81),
+ "reye": (55, 42),
+ }
+ else:
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=embedding,
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
+ )
+
+ algorithm = Distance()
+
+ return VanillaBiometricsPipeline(transformer, algorithm)
+
+
+def facenet_baseline(embedding, annotation_type, fixed_positions=None):
+ # DEFINE CROPPING
+ cropped_image_size = (160, 160)
+ cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
+
+ # ASSEMBLE TRANSFORMER
+ transformer = embedding_transformer(
+ cropped_image_size=cropped_image_size,
+ embedding=embedding,
+ cropped_positions=cropped_positions,
+ fixed_positions=fixed_positions,
+ color_channel="rgb",
+ annotator="mtcnn",
+ )
+
+ algorithm = Distance()
+
+ return VanillaBiometricsPipeline(transformer, algorithm)
diff --git a/bob/bio/face/config/baseline/tf2_inception_resnet.py b/bob/bio/face/config/baseline/tf2_inception_resnet.py
index 619bcf82..87862c7a 100644
--- a/bob/bio/face/config/baseline/tf2_inception_resnet.py
+++ b/bob/bio/face/config/baseline/tf2_inception_resnet.py
@@ -1,45 +1,22 @@
from bob.extension import rc
from bob.bio.face.embeddings.tf2_inception_resnet import InceptionResnetv2
-from bob.bio.face.preprocessor import FaceCrop
-from bob.bio.face.config.baseline.helpers import (
- lookup_config_from_database,
- dnn_default_cropping,
- embedding_transformer,
-)
-
-from sklearn.pipeline import make_pipeline
-from bob.pipelines.wrappers import wrap
-from bob.bio.base.pipelines.vanilla_biometrics import (
- Distance,
- VanillaBiometricsPipeline,
-)
+from bob.bio.face.config.baseline.helpers import lookup_config_from_database
+from bob.bio.face.config.baseline.templates import facenet_baseline
annotation_type, fixed_positions, memory_demanding = lookup_config_from_database()
def load(annotation_type, fixed_positions=None):
- # DEFINE CROPPING
- cropped_image_size = (160, 160)
- cropped_positions = dnn_default_cropping(cropped_image_size, annotation_type)
-
extractor_path = rc["bob.bio.face.tf2.casia-webface-inception-v2"]
embedding = InceptionResnetv2(
checkpoint_path=extractor_path, memory_demanding=memory_demanding
)
- # ASSEMBLE TRANSFORMER
- transformer = embedding_transformer(
- cropped_image_size=cropped_image_size,
+ return facenet_baseline(
embedding=embedding,
- cropped_positions=cropped_positions,
+ annotation_type=annotation_type,
fixed_positions=fixed_positions,
- color_channel="rgb",
- annotator="mtcnn",
)
- algorithm = Distance()
-
- return VanillaBiometricsPipeline(transformer, algorithm)
-
pipeline = load(annotation_type, fixed_positions)
transformer = pipeline.transformer
--
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